[Fix] Fix waymo converter (open-mmlab#2040)

* fix waymo converter

* [Fix] Update waymo converter and fix lint

* Update waymo_converter.py

* Update kitti_converter.py

* Update update_infos_to_v2.py

* revert

mmdet3d/datasets/convert_utils.py

@@ -296,7 +296,7 @@ def get_kitti_style_2d_boxes(info: dict,
  repro_rec['velocity'] = -1 # no velocity in KITTI
 
  center_3d = np.array(loc).reshape([1, 3])
- center_2d_with_depth = box_np_ops.points_cam2img(
+ center_2d_with_depth = points_cam2img(
  center_3d, camera_intrinsic, with_depth=True)
  center_2d_with_depth = center_2d_with_depth.squeeze().tolist()
 

mmdet3d/models/roi_heads/mask_heads/foreground_segmentation_head.py

@@ -3,14 +3,14 @@
 
 import torch
 from mmcv.cnn.bricks import build_norm_layer
+from mmdet.models.utils import multi_apply
 from mmengine.model import BaseModule
 from mmengine.structures import InstanceData
 from torch import nn as nn
 
 from mmdet3d.models.builder import build_loss
 from mmdet3d.registry import MODELS
 from mmdet3d.utils import InstanceList
-from mmdet.models.utils import multi_apply
 
 
 @MODELS.register_module()

mmdet3d/models/roi_heads/pv_rcnn_roi_head.py

@@ -2,15 +2,15 @@
 from typing import List, Optional
 
 import torch
+from mmdet.models.task_modules import AssignResult
+from mmdet.models.task_modules.samplers import SamplingResult
 from torch.nn import functional as F
 
 from mmdet3d.models.roi_heads.base_3droi_head import Base3DRoIHead
 from mmdet3d.registry import MODELS
 from mmdet3d.structures import bbox3d2roi
 from mmdet3d.structures.det3d_data_sample import SampleList
 from mmdet3d.utils import InstanceList
-from mmdet.models.task_modules import AssignResult
-from mmdet.models.task_modules.samplers import SamplingResult
 
 
 @MODELS.register_module()

tools/dataset_converters/update_infos_to_v2.py

@@ -80,9 +80,6 @@ def get_empty_lidar_points():
  num_pts_feats=None,
  # (str, optional): Path of LiDAR data file.
  lidar_path=None,
- # (list[list[float]]): Transformation matrix from lidar
- # or depth to image with shape [4, 4].
- lidar2img=None,
  # (list[list[float]], optional): Transformation matrix
  # from lidar to ego-vehicle
  # with shape [4, 4].
@@ -120,6 +117,9 @@ def get_empty_img_info():
  # matrix from camera to image with
  # shape [3, 3], [3, 4] or [4, 4].
  cam2img=None,
+ # (list[list[float]]): Transformation matrix from lidar
+ # or depth to image with shape [4, 4].
+ lidar2img=None,
  # (list[list[float]], optional) : Transformation
  # matrix from camera to ego-vehicle
  # with shape [4, 4].
@@ -159,7 +159,7 @@ def get_empty_standard_data_info(
 
  data_info = dict(
  # (str): Sample id of the frame.
- sample_id=None,
+ sample_idx=None,
  # (str, optional): '000010'
  token=None,
  **get_single_image_sweep(camera_types),

tools/dataset_converters/waymo_converter.py

@@ -69,10 +69,7 @@ def __init__(self,
  '_SIDE_LEFT',
  '_SIDE_RIGHT',
  ]
- self.lidar_list = [
- '_FRONT', '_FRONT_RIGHT', '_FRONT_LEFT', '_SIDE_RIGHT',
- '_SIDE_LEFT'
- ]
+ self.lidar_list = ['TOP', 'FRONT', 'SIDE_LEFT', 'SIDE_RIGHT', 'REAR']
  self.type_list = [
  'UNKNOWN', 'VEHICLE', 'PEDESTRIAN', 'SIGN', 'CYCLIST'
  ]
@@ -135,7 +132,8 @@ def convert_one(self, file_idx):
 
  self.save_image(frame, file_idx, frame_idx)
  self.save_calib(frame, file_idx, frame_idx)
- self.save_lidar(frame, file_idx, frame_idx)
+ if 'testing_3d_camera_only_detection' not in self.load_dir:
+ self.save_lidar(frame, file_idx, frame_idx)
  self.save_pose(frame, file_idx, frame_idx)
  self.save_timestamp(frame, file_idx, frame_idx)
 
@@ -441,7 +439,6 @@ def create_folder(self):
  dir_list1 = [
  self.label_all_save_dir,
  self.calib_save_dir,
- self.point_cloud_save_dir,
  self.pose_save_dir,
  self.timestamp_save_dir,
  ]
@@ -451,10 +448,12 @@ def create_folder(self):
  dir_list2.append(self.cam_sync_label_save_dir)
  else:
  dir_list1 = [
- self.calib_save_dir, self.point_cloud_save_dir,
- self.pose_save_dir, self.timestamp_save_dir
+ self.calib_save_dir, self.pose_save_dir,
+ self.timestamp_save_dir
  ]
  dir_list2 = [self.image_save_dir]
+ if 'testing_3d_camera_only_detection' not in self.load_dir:
+ dir_list1.append(self.point_cloud_save_dir)
  for d in dir_list1:
  mmengine.mkdir_or_exist(d)
  for d in dir_list2: